maven build config

make/maven/maven_darwin_cpu.mk

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+#-------------------------------------------------------------------------------
+#  Template configuration for compiling mxnet for making python wheel
+#-------------------------------------------------------------------------------
+
+#---------------------
+# choice of compiler
+#--------------------
+
+export CC = gcc
+export CXX = g++
+export NVCC = nvcc
+
+# whether compile with options for MXNet developer
+DEV = 0
+
+# whether compile with debug
+DEBUG = 0
+
+# whether compiler with profiler
+USE_PROFILER = 1
+
+# whether to turn on signal handler (e.g. segfault logger)
+USE_SIGNAL_HANDLER = 0
+
+# the additional link flags you want to add
+ADD_LDFLAGS += -L$(DEPS_PATH)/lib -lpng -ltiff -lz -framework CoreFoundation -framework Security  -Wl,-exported_symbols_list,$(CURDIR)/make/config/libmxnet.sym,-rpath,'$${ORIGIN}',-dead_strip
+
+# the additional compile flags you want to add
+ADD_CFLAGS += -I$(DEPS_PATH)/include -ffunction-sections -fdata-sections
+
+#---------------------------------------------
+# matrix computation libraries for CPU/GPU
+#---------------------------------------------
+
+# choose the version of blas you want to use
+# can be: mkl, blas, atlas, openblas
+# in default use atlas for linux while apple for osx
+USE_BLAS=apple
+
+# whether use opencv during compilation
+# you can disable it, however, you will not able to use
+# imbin iterator
+USE_OPENCV = 1
+
+# whether use CUDA during compile
+USE_CUDA = 0
+
+# add the path to CUDA library to link and compile flag
+# if you have already add them to environment variable, leave it as NONE
+# USE_CUDA_PATH = /usr/local/cuda
+USE_CUDA_PATH = NONE
+
+# whether use CuDNN R3 library
+USE_CUDNN = 0
+
+# CUDA architecture setting: going with all of them.
+# For CUDA < 6.0, comment the *_50 lines for compatibility.
+# CUDA_ARCH :=
+
+# whether use cuda runtime compiling for writing kernels in native language (i.e. Python)
+USE_NVRTC = 0
+
+# use openmp for parallelization
+USE_OPENMP = 0
+USE_OPERATOR_TUNING = 1
+USE_LIBJPEG_TURBO = 1
+
+
+# MKL ML Library for Intel CPU/Xeon Phi
+# Please refer to MKL_README.md for details
+
+# whether use MKL-DNN library
+USE_MKLDNN = 0
+
+# MKL ML Library folder, need to be root for /usr/local
+# Change to User Home directory for standard user
+# For USE_BLAS!=mkl only
+MKLML_ROOT=/usr/local
+
+# whether use MKL2017 library
+USE_MKL2017 = 0
+
+# whether use MKL2017 experimental feature for high performance
+# Prerequisite USE_MKL2017=1
+USE_MKL2017_EXPERIMENTAL = 0
+
+# whether use NNPACK library
+USE_NNPACK = 0
+
+# whether use lapack during compilation
+# only effective when compiled with blas versions openblas/apple/atlas/mkl
+USE_LAPACK = 1
+
+# path to lapack library in case of a non-standard installation
+USE_LAPACK_PATH = $(DEPS_PATH)/lib
+
+# add path to intel library, you may need it for MKL, if you did not add the path
+# to environment variable
+USE_INTEL_PATH = NONE
+
+# If use MKL, choose static link automatically to allow python wrapper
+ifeq ($(USE_BLAS), mkl)
+USE_STATIC_MKL = 1
+else
+USE_STATIC_MKL = NONE
+endif
+
+#----------------------------
+# Settings for power and arm arch
+#----------------------------
+ARCH := $(shell uname -a)
+ifneq (,$(filter $(ARCH), armv6l armv7l powerpc64le ppc64le aarch64))
+	USE_SSE=0
+else
+	USE_SSE=1
+endif
+
+#----------------------------
+# distributed computing
+#----------------------------
+
+# whether or not to enable multi-machine supporting
+USE_DIST_KVSTORE = 1
+
+# whether or not allow to read and write HDFS directly. If yes, then hadoop is
+# required
+USE_HDFS = 0
+
+# path to libjvm.so. required if USE_HDFS=1
+LIBJVM=$(JAVA_HOME)/jre/lib/amd64/server
+
+# whether or not allow to read and write AWS S3 directly. If yes, then
+# libcurl4-openssl-dev is required, it can be installed on Ubuntu by
+# sudo apt-get install -y libcurl4-openssl-dev
+USE_S3 = 1
+
+#----------------------------
+# additional operators
+#----------------------------
+
+# path to folders containing projects specific operators that you don't want to put in src/operators
+EXTRA_OPERATORS =
+
+
+#----------------------------
+# plugins
+#----------------------------
+
+# whether to use caffe integration. This requires installing caffe.
+# You also need to add CAFFE_PATH/build/lib to your LD_LIBRARY_PATH
+# CAFFE_PATH = $(HOME)/caffe
+# MXNET_PLUGINS += plugin/caffe/caffe.mk
+
+# whether to use torch integration. This requires installing torch.
+# You also need to add TORCH_PATH/install/lib to your LD_LIBRARY_PATH
+# TORCH_PATH = $(HOME)/torch
+# MXNET_PLUGINS += plugin/torch/torch.mk
+
+# WARPCTC_PATH = $(HOME)/warp-ctc
+# MXNET_PLUGINS += plugin/warpctc/warpctc.mk
+
+# whether to use sframe integration. This requires build sframe
+# [email protected]:dato-code/SFrame.git
+# SFRAME_PATH = $(HOME)/SFrame
+# MXNET_PLUGINS += plugin/sframe/plugin.mk

make/maven/maven_linux_cpu.mk

@@ -0,0 +1,165 @@
+#-------------------------------------------------------------------------------
+#  Template configuration for compiling mxnet for making python wheel
+#-------------------------------------------------------------------------------
+
+#---------------------
+# choice of compiler
+#--------------------
+
+export CC = gcc
+export CXX = g++
+export NVCC = nvcc
+
+# whether compile with options for MXNet developer
+DEV = 0
+
+# whether compile with debug
+DEBUG = 0
+
+# whether compiler with profiler
+USE_PROFILER = 1
+
+# whether to turn on signal handler (e.g. segfault logger)
+USE_SIGNAL_HANDLER = 0
+
+# the additional link flags you want to add
+ADD_LDFLAGS += -L$(DEPS_PATH)/lib -lpng -ltiff -ljpeg -lz -lgfortran -ldl -Wl,--version-script=$(CURDIR)/make/config/libmxnet.ver,-rpath,'$${ORIGIN}',--gc-sections
+
+# the additional compile flags you want to add
+ADD_CFLAGS += -I$(DEPS_PATH)/include -ffunction-sections -fdata-sections
+
+#---------------------------------------------
+# matrix computation libraries for CPU/GPU
+#---------------------------------------------
+
+# choose the version of blas you want to use
+# can be: mkl, blas, atlas, openblas
+# in default use atlas for linux while apple for osx
+USE_BLAS=openblas
+
+# whether use opencv during compilation
+# you can disable it, however, you will not able to use
+# imbin iterator
+USE_OPENCV = 1
+
+# whether use CUDA during compile
+USE_CUDA = 0
+
+# add the path to CUDA library to link and compile flag
+# if you have already add them to environment variable, leave it as NONE
+# USE_CUDA_PATH = /usr/local/cuda
+USE_CUDA_PATH = NONE
+
+# whether use CuDNN R3 library
+USE_CUDNN = 0
+
+# CUDA architecture setting: going with all of them.
+# For CUDA < 6.0, comment the *_50 lines for compatibility.
+# CUDA_ARCH :=
+
+# whether use cuda runtime compiling for writing kernels in native language (i.e. Python)
+USE_NVRTC = 0
+
+# use openmp for parallelization
+USE_OPENMP = 1
+USE_OPERATOR_TUNING = 1
+USE_LIBJPEG_TURBO = 1
+
+# whether use MKL-DNN library
+USE_MKLDNN = 0
+
+
+# MKL ML Library for Intel CPU/Xeon Phi
+# Please refer to MKL_README.md for details
+
+# MKL ML Library folder, need to be root for /usr/local
+# Change to User Home directory for standard user
+# For USE_BLAS!=mkl only
+MKLML_ROOT=/usr/local
+
+# whether use MKL2017 library
+USE_MKL2017 = 0
+
+# whether use MKL2017 experimental feature for high performance
+# Prerequisite USE_MKL2017=1
+USE_MKL2017_EXPERIMENTAL = 0
+
+# whether use NNPACK library
+USE_NNPACK = 0
+
+# whether use lapack during compilation
+# only effective when compiled with blas versions openblas/apple/atlas/mkl
+USE_LAPACK = 1
+
+# path to lapack library in case of a non-standard installation
+USE_LAPACK_PATH = $(DEPS_PATH)/lib
+
+# add path to intel library, you may need it for MKL, if you did not add the path
+# to environment variable
+USE_INTEL_PATH = NONE
+
+# If use MKL, choose static link automatically to allow python wrapper
+ifeq ($(USE_BLAS), mkl)
+USE_STATIC_MKL = 1
+else
+USE_STATIC_MKL = NONE
+endif
+
+#----------------------------
+# Settings for power and arm arch
+#----------------------------
+ARCH := $(shell uname -a)
+ifneq (,$(filter $(ARCH), armv6l armv7l powerpc64le ppc64le aarch64))
+	USE_SSE=0
+else
+	USE_SSE=1
+endif
+
+#----------------------------
+# distributed computing
+#----------------------------
+
+# whether or not to enable multi-machine supporting
+USE_DIST_KVSTORE = 1
+
+# whether or not allow to read and write HDFS directly. If yes, then hadoop is
+# required
+USE_HDFS = 0
+
+# path to libjvm.so. required if USE_HDFS=1
+LIBJVM=$(JAVA_HOME)/jre/lib/amd64/server
+
+# whether or not allow to read and write AWS S3 directly. If yes, then
+# libcurl4-openssl-dev is required, it can be installed on Ubuntu by
+# sudo apt-get install -y libcurl4-openssl-dev
+USE_S3 = 1
+
+#----------------------------
+# additional operators
+#----------------------------
+
+# path to folders containing projects specific operators that you don't want to put in src/operators
+EXTRA_OPERATORS =
+
+
+#----------------------------
+# plugins
+#----------------------------
+
+# whether to use caffe integration. This requires installing caffe.
+# You also need to add CAFFE_PATH/build/lib to your LD_LIBRARY_PATH
+# CAFFE_PATH = $(HOME)/caffe
+# MXNET_PLUGINS += plugin/caffe/caffe.mk
+
+# whether to use torch integration. This requires installing torch.
+# You also need to add TORCH_PATH/install/lib to your LD_LIBRARY_PATH
+# TORCH_PATH = $(HOME)/torch
+# MXNET_PLUGINS += plugin/torch/torch.mk
+
+# WARPCTC_PATH = $(HOME)/warp-ctc
+# MXNET_PLUGINS += plugin/warpctc/warpctc.mk
+
+# whether to use sframe integration. This requires build sframe
+# [email protected]:dato-code/SFrame.git
+# SFRAME_PATH = $(HOME)/SFrame
+# MXNET_PLUGINS += plugin/sframe/plugin.mk